AAAI Publications, Twenty-Seventh AAAI Conference on Artificial Intelligence

Font Size: 
Learning to Rank Effective Paraphrases from Query Logs for Community Question Answering
Alejandro Figueroa, Guenter Neumann

Last modified: 2013-06-29

Abstract


We present a novel method for ranking query paraphrases for effective search in community question answering (cQA). The method uses query logs from Yahoo! Search and Yahoo! Answers for automatically extracting a corpus of paraphrases of queries and questions using the query-question click history. Elements of this corpus are automatically ranked according to recall and mean reciprocal rank, and then used for learning two independent learning to rank models (SVMRank), whereby a set of new query paraphrases can be scored according to recall and MRR. We perform several automatic evaluation procedures using cross-validation for analyzing the behavior of various aspects of our learned ranking functions, which show that our method is useful and effective for search in cQA.

Keywords


Question Answering on the Web; Community Question Answering; Learning to Rank; Machine Learning; Paraphrases; Ranking; Effective Paraphrases;

Full Text: PDF